Digital scanners are well-known devices for taking images of articles such as paper documents and objects including for example payment cards and converting the images into electronic files. Although scanners have a variety of general and specific uses, they are most commonly used to scan documents in order to consolidate records, create paperless work environments and/or facilitate the electronic transmission of information.
Scanners vary in design and sophistication, but generally all comprise an elongate light source and a grid or series of sensors for receiving light that is reflected off of the surface of the article being scanned. The data from the sensors is collected by a processor operating under control of scanner software and stored as a digital image file typically in JPEG, BMP or GIF format. If the scanner is coupled to a computer or to a local or wide area network, the digital image file is typically made available to the computer or to network devices for storage and/or further processing.
When scanning credit cards or other objects having embossed (stamped) characters thereon using a general-purpose scanner, some challenges present themselves. For example, due to the height of embossed characters, the distance between the sensors and the base surface of the card being scanned is increased. This increase in distance consequently produces images that are significantly lower in overall intensity because of the decrease in the amount of light received by the sensors. In other words, the images tend to have pixels with intensity values that lean toward the dark region of the greyscale spectrum. In some cases, the edges of embossed characters that extend perpendicular to the longitudinal axis of the light source brightly stand out in the images, making the embossed characters easy to discern from the background. Unfortunately, more often the scanner will fail to capture these bright edge contrasts, resulting in a dark image having characters therein that are very difficult to discern from the background.
Prior art attempts to improve the contrast in images of articles having embossed characters thereon have, in some cases, focused on improvements to the image capture hardware and sensor configurations. For example, U.S. Pat. No. 3,937,928 to Sasaki et al. discloses an embossed card reader comprising a card transport table upon which a slit plate having two slits is placed. When a card having embossed characters is supported by the transport table, the card is illuminated through one of the slits. Light reflecting off the card passes through the other slit to an array of parallel aligned, light-sensitive elements. The light-sensitive elements are sequentially scanned while light is passed over the embossed characters on the card in order to recognize the characters on the card.
U.S. Pat. No. 3,939,327 to Humphrey discloses an optical reading apparatus and method for identifying alpha-numeric indicia on credit cards and the like. Indicia are read by conducting light from a source to the surface of the credit card by a light conducting rod. Light reflected from the surface is conducted to a photo sensor by a second light conducting rod. The first and second light conducting rods are arranged so that reflected light is transmitted to the photo sensor when incident light from the source impinges on the planar surface of the credit card. However, when light from the source impinges on an embossed or debossed portion of indicia, it is no longer reflected to the second light conducting rod. Hence the photo sensor produces a change in its output indicative of the absence of light allowing the indicia on the card to be recognized.
Prior art attempts to improve the contrast in images of articles having embossed characters thereon have also focused on improvements to image post-processing. For example, U.S. Pat. No. 6,628,808 to Bach et al. discloses a method for increasing the reliability of optical character verification systems, particularly when used with images where there is no sharp division between the foreground and the background. With such images, it is difficult to resolve a source grayscale image into a simple bi-level image. During the method, pixel intensity is corrected for the purpose of subsequent character recognition by normalizing the pixel intensities across an available dynamic range.
U.S. Pat. No. 6,731,821 to Maurer et al. discloses a system and method of increasing compressibility of image data by selectively smoothing the image data while preserving edges using variable contrast stretching. While smoothing is performed using an edge preserving image smoothing/de-noising technique, sharpening of edges is performed using variable contrast stretching based on the pre-smoothed image data. During the method, the dynamic intensity range of the entire image over the complete dynamic range of the image capturing device is normalized.
The above described methods focus particularly on making character data in images more machine-readable, primarily for the purpose of optical character recognition (OCR) and file compression. Unfortunately these techniques do not generally yield images that are significantly easier for humans to read.
It is therefore an object of the present invention to provide a novel method and apparatus for increasing contrast in a digital image.